Constructing Confidence Intervals
|
|
- Buck Long
- 7 years ago
- Views:
Transcription
1 Lab 13 Constructing Confidence Intervals In this lab, we will construct and visualize confidence intervals for different sample sizes and different levels of confidence. Sampling Data Please load the following dataset into Stata.. use We have thirty variables regarding stocks listed in the Standard and Poor s 500. We will focus on the percentage return during a twenty-six week period (pctchg26wks).. histogram pctchg26wks, norm. summarize pctchg26wks Looking at the statistical summary of this variable, we can see that the average stock value in the Standard and Poor s 500 dropped 12.6% during this 26 week period, with a maximum loss of 92% to a maximum gain of 99%. The histogram shows us that the population distribution is approximately normal. 88
2 We are going to use this data set and this variable pctchg26wks to test the theory of confidence intervals. In general, the way we construct a confidence interval is by obtaining a sample and then constructing an interval around the mean of that sample. This interval is intended to give us an estimate of the true population mean, which in general is unknown. We are going to use a sort of reverse psychology. We know the true population mean for the percentage return for the S & P s 500 stocks over this particular 26 week period and we know the true population standard deviation (23.6) of this variable. The dataset we loaded contains the entire population! We can test the theory of confidence intervals by taking samples of the dataset and constructing confidence intervals around the means of those samples. Then we can check and see if these confidence intervals, that we estimated, contain the true mean or not. We will use a statistical technique called bootstrapping. This simply means we will take simple random samples of the dataset with replacement. For the purposes of constructing confidence intervals, we are not really interested in the sample itself, we are more interested in the mean of the sample. The bootstrap command will bypass the output of individual samples and give us the sample mean for each sample it draws. The bootstrap command takes as many samples as you want of the specified variable and then takes the mean of each of those samples. It outputs a new dataset, where each observation represents a single sample from the original population. *** Important *** This new file should be saved into your home directory. To ensure this occurs, change your working directory by clicking on the File menu and selecting Set Working Folder. The default is your Documents folder. This is the correct location, so click on the Choose button. Now any files you create will show up in your documents folder. Now to ensure we truly are taking random samples, we want to randomly set a seed for Stata to start from.. set seed YOUR STUDENT ID NUMBER 89
3 Finally, we are ready to start sampling.. bootstrap "summarize pctchg26wks" "r(mean)", reps(100) size(16) dots saving (cidata) replace This command will take 100 random samples of size 16 and calculate the mean of the variable pctchg26wks for each sample. It will then save this information in a file called cidata.dta. Now we want to open up this dataset we just created and construct a confidence interval for each of the 100 samples.. use cidata, clear When we issue the command. list we see one variable bs 1 (short for bootstrap one), which is a list of 100 means from the 100 samples of size 16 that we selected from the S&P s 500 stocks. We can look at the distribution of these sample means. (Remember the Central Limit Theorem tells us that as the size of our samples increase, the distribution of the sample means becomes more and more normally distributed.). histogram bs 1, norm Question 1: How does this distribution compare to the distribution of pctchg26wks? Constructing & Visualizing Confidence Intervals For each sample mean, we want to generate an appropriate confidence interval. Recall the formula for constructing a confidence interval when the standard deviation σ is known. 90
4 x ± z σ n We know σ (the true population standard deviation) is We also know that n (the size of the sample) is 16. We want to explore what happens to confidence intervals when we change our level of confidence. We will create 68%, 85%, and 93% confidence intervals for each of our 100 samples. The technique we will use is to create the lower bound of the confidence interval ( x z σ n ) and then the upper bound of the confidence interval ( x + z σ n ). For a 68% confidence interval, z = The variable bs 1 contains all our sample means ( x).. generate lower68 = bs * /sqrt(16). generate upper68 = bs * /sqrt(16) Note: If you make a mistake when generating your new variables, use the drop command to remove variables from your dataset and reissue the correct command. For example, if I messed up and typed generate upper68 = bs * /sqrt(160), then I could remove this variable by typing drop upper68 and then regenerate the variable correctly.. list Look at the data. As you can see, the variables lower68 and upper68 form an interval surrounding the bs 1 variable. Question 2: We know that the true mean for this population is 12.6%. According to the theory of confidence intervals, how many of these confidence intervals should contain the true mean? We can actually determine exactly how many of our confidence intervals contain the true mean. 91
5 . count if lower68 <= & upper68 >= This command counts the value only if the lower bound is below the true population mean and the upper bound is above the true population mean. Question 3: How many of your 68% confidence intervals captured the true population mean? Does this number surprise you or does it seem about right? We can visualize the confidence intervals by plotting them side by side. To do this we must create a helper variable.... gen num = n Then issue the following graph command.. twoway (rcap upper68 lower68 num) (scatter bs 1 num, msymbol(o)), yline( ) title("100 68% confidence intervals from samples n=16") Each of your confidence intervals pop up in the resulting graph. Each line corresponds to exactly one confidence interval and the dot in the middle corresponds to the x for that confidence interval. We inserted a line going through the confidence intervals at the true population mean of As you can see, some of the confidence intervals capture this true mean and others don t. This is the caveat of confidence intervals. In a real life setting, we have no way of knowing if the one sample we have is one of the cases that does not capture the true mean! This is why large sample sizes and high levels of confidence are so important. If you want, you can make this graph even fancier. Wouldn t it be nice if the graph some how highlighted the confidence intervals that did not capture the true population mean?. twoway (rcap upper68 lower68 num) (rcap upper68 lower68 num if upper68 < lower68 > , blcolor(red)) (scatter bs 1 num, msymbol(o)), yline( ) title("100 68% confidence intervals from samples n=16") 92
6 This basically colors the interval red if the upper bound is below or the lower bound is above Question 4: What is the length of a 68% confidence interval in this setting? Next we repeat the process by generating 85% and then 93% confidence intervals. For the 68% confidence interval, we told you z, if we hadn t, you could have looked it up on the standard normal table or remembered the rule. Stata gives us another option. Using the invnorm function, if we give Stata a probability p, it will return the z-value such that the area below it will equal p. For example, suppose you had not been given the z value for a 68% confidence interval and you didn t know the rule. To determine the z value, first we must divide 1.68 by 2 to determine the correct probability we want to look up, and then we input that value into the invnorm function.. di (1 -.68)/2. di invnorm(.16) As you can see, Stata returns a value of.9945 or rounded even further 1. We, of course, use the positive value for z. Stata Note: di is the Stata equivalent to a calculator; it is short for display. 93
7 Question 5: What is the z value for an 85% confidence interval? Question 6: What number will you be adding and subtracting to bs 1 to obtain a 85% confidence interval? Based on this, what will be the length of a 85% confidence interval? Construct variables lower85 and upper85 similarly to the way you constructed lower68 and upper68. Be sure you make the appropriate change in the formula. Question 7: According to theory, how many of your 85% confidence intervals are expected to capture the true population mean? How many of your 85% confidence intervals actually capture the true population mean? Create a graph, with the appropriate title, of your 85% confidence intervals. Repeat the process for 93% confidence intervals. Question 8: What is the z value for a 93% confidence interval? Question 9: According to theory, how many of your 93% confidence intervals are expected to capture the true population mean? How many of your 93% confidence intervals actually capture the true population mean? 94
8 Supplementary Section on Do-files This lab is a perfect example for when Stata do-files come in handy. The assignment for this lab is essentially a replication of the in-class portion of the lab. The main difference is you need to change the sample size n. A dofile is a file that contains one Stata command per line. When run, it executes each of the commands. You can type commands directly into a file, save it with the.do extension and then do it in Stata, but in our case there is an even easier way. Hold down the Control button on the keyboard and click on the Review window. You now have two options. First, Copy Review Contents to Dofile Editor. This will open the do-file editor window with the contents of the review window pasted in. Second, Save Review Contents.... This method allows you to save the file as a do-file. For the purpose of this lab, click on Save Review Contents... and save the file as cilab.do. Now type the following command.. doedit cilab This will bring up a text window with the commands you entered. A few corrections need to be made before this file will run. Add the option clear to the use command. In other words, the first line of your do-file should look like: use clear This is needed if data is already in Stata memory. The do-file won t run without it. Once you have added that option, re-save the do-file. The next step is more user dependent. You need to clean up any potential errors you made when working through the in-class portion of the lab. Try doing the do-file.. do cilab What happens? Does it run all the way through until you see end of do-file in green? Or do you get a red error message? If you encounter a red error message, you need to find the error in the do-file and remove it. 95
9 Basically, your do-file should consist of one correct command per line. Clean up your do-file until it runs through. Now to do the assignment, you need to change the sample size. First, we look at the same confidence intervals for sample size 36. Instead of losing the original do-file, save the do-file under a new name, such as cilab36.do. Now, change the appropriate commands in the do-file and maybe delete some unnecessary commands, such as the list commands. You can now run this do-file, but you may notice a problem. The graphs fly by! If you want to print or save any of the graphs, this may be a problem. You can avoid this by doing only part of your do-file at a time. Highlight the portion you want to do. Then click on the Do current file button in the do-file editor window. Only the portion highlighted will be processed. 96
10 Assignment What happens to the length of confidence intervals if we change the sample size n? What happens to the length of confidence intervals as we change the level of confidence? What happens to the distribution of bs 1 as we change the sample size n? Reload the original dataset and run a new bootstrap command, this time with samples of size 36. (You do not need to reset the seed, this only needs to be done once.) Question 10: How many of your confidence intervals catch the true population mean for each of the three levels of confidence when n = 36? Question 11: Are corresponding confidence intervals using samples of size 36 longer or shorter than those for samples of size 16? What happens if we use samples of size 100? Reload the original dataset and run a new bootstrap command using samples of size 100. Question 12: How many of your confidence intervals catch the true population mean for each of the three levels of confidence when n = 100? Question 13: Are corresponding confidence intervals using samples of size 100 longer or shorter than those for samples of size 36? Question 14: As we increase the confidence level from 68% to 85% to 93%, what happens to the length of our intervals? 97
11 Question 15: What happens to the distribution of bs 1 as the sample size increases from 16 to 36 to 100? Discuss the changes that occur to the mean and the spread. 98
Lab 11. Simulations. The Concept
Lab 11 Simulations In this lab you ll learn how to create simulations to provide approximate answers to probability questions. We ll make use of a particular kind of structure, called a box model, that
More informationBasics of STATA. 1 Data les. 2 Loading data into STATA
Basics of STATA This handout is intended as an introduction to STATA. STATA is available on the PCs in the computer lab as well as on the Unix system. Throughout, bold type will refer to STATA commands,
More informationScatter Plots with Error Bars
Chapter 165 Scatter Plots with Error Bars Introduction The procedure extends the capability of the basic scatter plot by allowing you to plot the variability in Y and X corresponding to each point. Each
More informationDealing with Data in Excel 2010
Dealing with Data in Excel 2010 Excel provides the ability to do computations and graphing of data. Here we provide the basics and some advanced capabilities available in Excel that are useful for dealing
More information6 3 The Standard Normal Distribution
290 Chapter 6 The Normal Distribution Figure 6 5 Areas Under a Normal Distribution Curve 34.13% 34.13% 2.28% 13.59% 13.59% 2.28% 3 2 1 + 1 + 2 + 3 About 68% About 95% About 99.7% 6 3 The Distribution Since
More informationHow to test and debug an ASP.NET application
Chapter 4 How to test and debug an ASP.NET application 113 4 How to test and debug an ASP.NET application If you ve done much programming, you know that testing and debugging are often the most difficult
More informationSPSS Manual for Introductory Applied Statistics: A Variable Approach
SPSS Manual for Introductory Applied Statistics: A Variable Approach John Gabrosek Department of Statistics Grand Valley State University Allendale, MI USA August 2013 2 Copyright 2013 John Gabrosek. All
More informationOpening, Importing and Saving Images
Opening, Importing and Saving Images This tutorial will help you to become familiar with how to open, import and save the various file types that the Make The Cut! (MTC!) software supports. You can find
More informationIntermediate PowerPoint
Intermediate PowerPoint Charts and Templates By: Jim Waddell Last modified: January 2002 Topics to be covered: Creating Charts 2 Creating the chart. 2 Line Charts and Scatter Plots 4 Making a Line Chart.
More informationDescriptive Statistics
Descriptive Statistics Descriptive statistics consist of methods for organizing and summarizing data. It includes the construction of graphs, charts and tables, as well various descriptive measures such
More informationGraphing Parabolas With Microsoft Excel
Graphing Parabolas With Microsoft Excel Mr. Clausen Algebra 2 California State Standard for Algebra 2 #10.0: Students graph quadratic functions and determine the maxima, minima, and zeros of the function.
More informationLesson 17: Margin of Error When Estimating a Population Proportion
Margin of Error When Estimating a Population Proportion Classwork In this lesson, you will find and interpret the standard deviation of a simulated distribution for a sample proportion and use this information
More informationUpdates to Graphing with Excel
Updates to Graphing with Excel NCC has recently upgraded to a new version of the Microsoft Office suite of programs. As such, many of the directions in the Biology Student Handbook for how to graph with
More informationHow to Make the Most of Excel Spreadsheets
How to Make the Most of Excel Spreadsheets Analyzing data is often easier when it s in an Excel spreadsheet rather than a PDF for example, you can filter to view just a particular grade, sort to view which
More informationGetting started with the Stata
Getting started with the Stata 1. Begin by going to a Columbia Computer Labs. 2. Getting started Your first Stata session. Begin by starting Stata on your computer. Using a PC: 1. Click on start menu 2.
More informationMgmt 469. Programming in Stata: Creating do-files
Mgmt 469 Programming in Stata: Creating do-files An important feature of any good research project is that the results should be reproducible. One way to make it easy to reproduce your results is to write
More informationA Guide to Using Excel in Physics Lab
A Guide to Using Excel in Physics Lab Excel has the potential to be a very useful program that will save you lots of time. Excel is especially useful for making repetitious calculations on large data sets.
More informationCALCULATIONS & STATISTICS
CALCULATIONS & STATISTICS CALCULATION OF SCORES Conversion of 1-5 scale to 0-100 scores When you look at your report, you will notice that the scores are reported on a 0-100 scale, even though respondents
More informationDirections for Frequency Tables, Histograms, and Frequency Bar Charts
Directions for Frequency Tables, Histograms, and Frequency Bar Charts Frequency Distribution Quantitative Ungrouped Data Dataset: Frequency_Distributions_Graphs-Quantitative.sav 1. Open the dataset containing
More informationHow to place an order through your Pleaser USA online account. 1. After logging into your account click on the desired brand to browse our inventory.
How to place an order through your Pleaser USA online account 1. After logging into your account click on the desired brand to browse our inventory. 2. Enter the desired quantity in the field below the
More informationPetrel TIPS&TRICKS from SCM
Petrel TIPS&TRICKS from SCM Knowledge Worth Sharing Histograms and SGS Modeling Histograms are used daily for interpretation, quality control, and modeling in Petrel. This TIPS&TRICKS document briefly
More informationNamed Memory Slots. Properties. CHAPTER 16 Programming Your App s Memory
CHAPTER 16 Programming Your App s Memory Figure 16-1. Just as people need to remember things, so do apps. This chapter examines how you can program an app to remember information. When someone tells you
More informationModule 2 Basic Data Management, Graphs, and Log-Files
AGRODEP Stata Training April 2013 Module 2 Basic Data Management, Graphs, and Log-Files Manuel Barron 1 and Pia Basurto 2 1 University of California, Berkeley, Department of Agricultural and Resource Economics
More informationUsing the Local Document Organizer in ProjectWise
Using the Local Document Organizer in ProjectWise ProjectWise stores copies of files on your local computer when you access them to provide the best performance over the state-wide network. The Local Document
More informationLecture 2 Mathcad Basics
Operators Lecture 2 Mathcad Basics + Addition, - Subtraction, * Multiplication, / Division, ^ Power ( ) Specify evaluation order Order of Operations ( ) ^ highest level, first priority * / next priority
More informationPsy 210 Conference Poster on Sex Differences in Car Accidents 10 Marks
Psy 210 Conference Poster on Sex Differences in Car Accidents 10 Marks Overview The purpose of this assignment is to compare the number of car accidents that men and women have. The goal is to determine
More informationExploratory Data Analysis with One and Two Variables
Exploratory Data Analysis with One and Two Variables Instructions for Lab #2 Statistics 111- Probability and Statistical Inference Lab Objective To explore data with histograms and scatter plots. Review
More informationExcel -- Creating Charts
Excel -- Creating Charts The saying goes, A picture is worth a thousand words, and so true. Professional looking charts give visual enhancement to your statistics, fiscal reports or presentation. Excel
More informationDoing Multiple Regression with SPSS. In this case, we are interested in the Analyze options so we choose that menu. If gives us a number of choices:
Doing Multiple Regression with SPSS Multiple Regression for Data Already in Data Editor Next we want to specify a multiple regression analysis for these data. The menu bar for SPSS offers several options:
More informationMicrosoft Excel Tutorial
Microsoft Excel Tutorial by Dr. James E. Parks Department of Physics and Astronomy 401 Nielsen Physics Building The University of Tennessee Knoxville, Tennessee 37996-1200 Copyright August, 2000 by James
More information1051-232 Imaging Systems Laboratory II. Laboratory 4: Basic Lens Design in OSLO April 2 & 4, 2002
05-232 Imaging Systems Laboratory II Laboratory 4: Basic Lens Design in OSLO April 2 & 4, 2002 Abstract: For designing the optics of an imaging system, one of the main types of tools used today is optical
More informationGestation Period as a function of Lifespan
This document will show a number of tricks that can be done in Minitab to make attractive graphs. We work first with the file X:\SOR\24\M\ANIMALS.MTP. This first picture was obtained through Graph Plot.
More informationRegression Clustering
Chapter 449 Introduction This algorithm provides for clustering in the multiple regression setting in which you have a dependent variable Y and one or more independent variables, the X s. The algorithm
More informationMulti-user Collaboration with Autodesk Revit Worksharing
AUTODESK REVIT WHITE PAPER Multi-user Collaboration with Autodesk Revit Worksharing Contents Contents... 1 Autodesk Revit Worksharing... 2 Starting Your First Multi-user Project... 2 Autodesk Revit Worksets...
More informationAdobe Acrobat 6.0 Professional
Adobe Acrobat 6.0 Professional Manual Adobe Acrobat 6.0 Professional Manual Purpose The will teach you to create, edit, save, and print PDF files. You will also learn some of Adobe s collaborative functions,
More informationInstalling and Using the Monte Carlo Simulation Excel Add-in. Software for
Installing and Using the Monte Carlo Simulation Excel Add-in Software for Introductory Econometrics By Humberto Barreto and Frank M. Howland hbarreto@depauw.edu and howlandf@wabash.edu (765) 658-4531 and
More informationUsing Microsoft Word. Working With Objects
Using Microsoft Word Many Word documents will require elements that were created in programs other than Word, such as the picture to the right. Nontext elements in a document are referred to as Objects
More informationFigure 1. An embedded chart on a worksheet.
8. Excel Charts and Analysis ToolPak Charts, also known as graphs, have been an integral part of spreadsheets since the early days of Lotus 1-2-3. Charting features have improved significantly over the
More informationOffline Files & Sync Center
bonus appendix Offline Files & Sync Center The offline files feature is designed for laptop lovers. It lets you carry off files that gerally live on your office network, so you can get some work done while
More informationConfidence Intervals for One Standard Deviation Using Standard Deviation
Chapter 640 Confidence Intervals for One Standard Deviation Using Standard Deviation Introduction This routine calculates the sample size necessary to achieve a specified interval width or distance from
More informationEXCEL Tutorial: How to use EXCEL for Graphs and Calculations.
EXCEL Tutorial: How to use EXCEL for Graphs and Calculations. Excel is powerful tool and can make your life easier if you are proficient in using it. You will need to use Excel to complete most of your
More informationAdvanced Microsoft Excel 2010
Advanced Microsoft Excel 2010 Table of Contents THE PASTE SPECIAL FUNCTION... 2 Paste Special Options... 2 Using the Paste Special Function... 3 ORGANIZING DATA... 4 Multiple-Level Sorting... 4 Subtotaling
More informationMigrating to Excel 2010 from Excel 2003 - Excel - Microsoft Office 1 of 1
Migrating to Excel 2010 - Excel - Microsoft Office 1 of 1 In This Guide Microsoft Excel 2010 looks very different, so we created this guide to help you minimize the learning curve. Read on to learn key
More informationABSORBENCY OF PAPER TOWELS
ABSORBENCY OF PAPER TOWELS 15. Brief Version of the Case Study 15.1 Problem Formulation 15.2 Selection of Factors 15.3 Obtaining Random Samples of Paper Towels 15.4 How will the Absorbency be measured?
More informationThe Normal Distribution
Chapter 6 The Normal Distribution 6.1 The Normal Distribution 1 6.1.1 Student Learning Objectives By the end of this chapter, the student should be able to: Recognize the normal probability distribution
More information0 Introduction to Data Analysis Using an Excel Spreadsheet
Experiment 0 Introduction to Data Analysis Using an Excel Spreadsheet I. Purpose The purpose of this introductory lab is to teach you a few basic things about how to use an EXCEL 2010 spreadsheet to do
More informationAccess Tutorial 1 Creating a Database
Access Tutorial 1 Creating a Database Microsoft Office 2013 Objectives Session 1.1 Learn basic database concepts and terms Start and exit Access Explore the Microsoft Access window and Backstage view Create
More informationUsing Excel for Data Manipulation and Statistical Analysis: How-to s and Cautions
2010 Using Excel for Data Manipulation and Statistical Analysis: How-to s and Cautions This document describes how to perform some basic statistical procedures in Microsoft Excel. Microsoft Excel is spreadsheet
More information5. Correlation. Open HeightWeight.sav. Take a moment to review the data file.
5. Correlation Objectives Calculate correlations Calculate correlations for subgroups using split file Create scatterplots with lines of best fit for subgroups and multiple correlations Correlation The
More informationNormal distributions in SPSS
Normal distributions in SPSS Bro. David E. Brown, BYU Idaho Department of Mathematics February 2, 2012 1 Calculating probabilities and percents from measurements: The CDF.NORMAL command 1. Go to the Variable
More informationEXCEL PIVOT TABLE David Geffen School of Medicine, UCLA Dean s Office Oct 2002
EXCEL PIVOT TABLE David Geffen School of Medicine, UCLA Dean s Office Oct 2002 Table of Contents Part I Creating a Pivot Table Excel Database......3 What is a Pivot Table...... 3 Creating Pivot Tables
More informationHow to Win the Stock Market Game
How to Win the Stock Market Game 1 Developing Short-Term Stock Trading Strategies by Vladimir Daragan PART 1 Table of Contents 1. Introduction 2. Comparison of trading strategies 3. Return per trade 4.
More informationExample: Find the expected value of the random variable X. X 2 4 6 7 P(X) 0.3 0.2 0.1 0.4
MATH 110 Test Three Outline of Test Material EXPECTED VALUE (8.5) Super easy ones (when the PDF is already given to you as a table and all you need to do is multiply down the columns and add across) Example:
More informationPresentations and PowerPoint
V-1.1 PART V Presentations and PowerPoint V-1.2 Computer Fundamentals V-1.3 LESSON 1 Creating a Presentation After completing this lesson, you will be able to: Start Microsoft PowerPoint. Explore the PowerPoint
More informationXPost: Excel Workbooks for the Post-estimation Interpretation of Regression Models for Categorical Dependent Variables
XPost: Excel Workbooks for the Post-estimation Interpretation of Regression Models for Categorical Dependent Variables Contents Simon Cheng hscheng@indiana.edu php.indiana.edu/~hscheng/ J. Scott Long jslong@indiana.edu
More informationShortcut Keystrokes in OS X by Phil Russell
Shortcut Keystrokes in OS X by Phil Russell Is this you? You close a window or document by clicking the close box at upper left of the window or document. You create a new folder by mousing to the File
More informationGetting started in Excel
Getting started in Excel Disclaimer: This guide is not complete. It is rather a chronicle of my attempts to start using Excel for data analysis. As I use a Mac with OS X, these directions may need to be
More informationPoint and Interval Estimates
Point and Interval Estimates Suppose we want to estimate a parameter, such as p or µ, based on a finite sample of data. There are two main methods: 1. Point estimate: Summarize the sample by a single number
More informationIntroduction to RStudio
Introduction to RStudio (v 1.3) Oscar Torres-Reyna otorres@princeton.edu August 2013 http://dss.princeton.edu/training/ Introduction RStudio allows the user to run R in a more user-friendly environment.
More informationData representation and analysis in Excel
Page 1 Data representation and analysis in Excel Let s Get Started! This course will teach you how to analyze data and make charts in Excel so that the data may be represented in a visual way that reflects
More informationProbability Distributions
CHAPTER 5 Probability Distributions CHAPTER OUTLINE 5.1 Probability Distribution of a Discrete Random Variable 5.2 Mean and Standard Deviation of a Probability Distribution 5.3 The Binomial Distribution
More informationAdvanced Excel Charts : Tables : Pivots : Macros
Advanced Excel Charts : Tables : Pivots : Macros Charts In Excel, charts are a great way to visualize your data. However, it is always good to remember some charts are not meant to display particular types
More informationINTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA)
INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA) As with other parametric statistics, we begin the one-way ANOVA with a test of the underlying assumptions. Our first assumption is the assumption of
More informationHYPOTHESIS TESTING WITH SPSS:
HYPOTHESIS TESTING WITH SPSS: A NON-STATISTICIAN S GUIDE & TUTORIAL by Dr. Jim Mirabella SPSS 14.0 screenshots reprinted with permission from SPSS Inc. Published June 2006 Copyright Dr. Jim Mirabella CHAPTER
More informationOrganizing image files in Lightroom part 2
Organizing image files in Lightroom part 2 Hopefully, after our last issue, you've spent some time working on your folder structure and now have your images organized to be easy to find. Whether you have
More informationPodcasting with Audacity
Podcasting with Audacity Table of Contents Introduction... 1 Why Podcast?... 2 Audacity Set-Up... 2 Installation... 2 Configuration... 2 Audacity Intro... 3 Adding tracks... 4 Prepare to Start Recording...
More informationOne-Way ANOVA using SPSS 11.0. SPSS ANOVA procedures found in the Compare Means analyses. Specifically, we demonstrate
1 One-Way ANOVA using SPSS 11.0 This section covers steps for testing the difference between three or more group means using the SPSS ANOVA procedures found in the Compare Means analyses. Specifically,
More informationUSING EXCEL ON THE COMPUTER TO FIND THE MEAN AND STANDARD DEVIATION AND TO DO LINEAR REGRESSION ANALYSIS AND GRAPHING TABLE OF CONTENTS
USING EXCEL ON THE COMPUTER TO FIND THE MEAN AND STANDARD DEVIATION AND TO DO LINEAR REGRESSION ANALYSIS AND GRAPHING Dr. Susan Petro TABLE OF CONTENTS Topic Page number 1. On following directions 2 2.
More informationMARS STUDENT IMAGING PROJECT
MARS STUDENT IMAGING PROJECT Data Analysis Practice Guide Mars Education Program Arizona State University Data Analysis Practice Guide This set of activities is designed to help you organize data you collect
More informationDescribing, Exploring, and Comparing Data
24 Chapter 2. Describing, Exploring, and Comparing Data Chapter 2. Describing, Exploring, and Comparing Data There are many tools used in Statistics to visualize, summarize, and describe data. This chapter
More informationEngineering Problem Solving and Excel. EGN 1006 Introduction to Engineering
Engineering Problem Solving and Excel EGN 1006 Introduction to Engineering Mathematical Solution Procedures Commonly Used in Engineering Analysis Data Analysis Techniques (Statistics) Curve Fitting techniques
More informationLabVIEW Day 6: Saving Files and Making Sub vis
LabVIEW Day 6: Saving Files and Making Sub vis Vern Lindberg You have written various vis that do computations, make 1D and 2D arrays, and plot graphs. In practice we also want to save that data. We will
More informationChapter 2: Descriptive Statistics
Chapter 2: Descriptive Statistics **This chapter corresponds to chapters 2 ( Means to an End ) and 3 ( Vive la Difference ) of your book. What it is: Descriptive statistics are values that describe the
More informationTime Billing. Chapter 1: Time Billing Activities Overview 563. Chapter 2: Creating activities 569. Chapter 3: Changing activities 574
Table of Contents Chapter 1: Time Billing Activities Overview 563 Creating activities 563 Changing activities 566 Removing or inactivating activities 567 Chapter 2: Creating activities 569 Step 1: Create
More informationYears after 2000. US Student to Teacher Ratio 0 16.048 1 15.893 2 15.900 3 15.900 4 15.800 5 15.657 6 15.540
To complete this technology assignment, you should already have created a scatter plot for your data on your calculator and/or in Excel. You could do this with any two columns of data, but for demonstration
More informationSetting Up Windows Perfmon to Collect Performance Data
Setting Up Windows Perfmon to Collect Performance Data In order to provide a comprehensive view of your environment, pick the busiest week of a typical month to collect your disk performance data. To set
More informationExcel 2007: Basics Learning Guide
Excel 2007: Basics Learning Guide Exploring Excel At first glance, the new Excel 2007 interface may seem a bit unsettling, with fat bands called Ribbons replacing cascading text menus and task bars. This
More informationRegistry Tuner. Software Manual
Registry Tuner Software Manual Table of Contents Introduction 1 System Requirements 2 Frequently Asked Questions 3 Using the Lavasoft Registry Tuner 5 Scan and Fix Registry Errors 7 Optimize Registry
More informationLife after Lotus Notes
Welcome Google Apps Welcome to Gmail! Now that you ve switched from Lotus Notes to, here are some tips on beginning to use Gmail and your other new Apps. What s Different? Here are some of the differences
More informationSummary of important mathematical operations and formulas (from first tutorial):
EXCEL Intermediate Tutorial Summary of important mathematical operations and formulas (from first tutorial): Operation Key Addition + Subtraction - Multiplication * Division / Exponential ^ To enter a
More informationL OCUTOUR. Get Ready to Spell! MULTIMEDIA COGNITIVE REHABILITATION
L OCUTOUR MULTIMEDIA COGNITIVE REHABILITATION Get Ready to Spell! Get Ready to Spell! Why Use This Program? This program is based on the observation that we learn by repetition. Many of the activities
More informationIntroduction to Exploratory Data Analysis
Introduction to Exploratory Data Analysis A SpaceStat Software Tutorial Copyright 2013, BioMedware, Inc. (www.biomedware.com). All rights reserved. SpaceStat and BioMedware are trademarks of BioMedware,
More informationSPSS Workbook 1 Data Entry : Questionnaire Data
TEESSIDE UNIVERSITY SCHOOL OF HEALTH & SOCIAL CARE SPSS Workbook 1 Data Entry : Questionnaire Data Prepared by: Sylvia Storey s.storey@tees.ac.uk SPSS data entry 1 This workbook is designed to introduce
More informationYour Personal Trading Journal
Your Personal Trading Journal This guide provides instructions for the setup and helps you getting started with your Edgewonk trading journal. It is recommended that you read it thoroughly to fully leverage
More informationData Preparation in SPSS
Data Preparation in SPSS Jamie DeCoster Center for Advanced Study of Teaching and Learning University of Virginia 350 Old Ivy Way Charlottesville, VA 22903 August 15, 2012 If you wish to cite the contents
More informationModule 3: Correlation and Covariance
Using Statistical Data to Make Decisions Module 3: Correlation and Covariance Tom Ilvento Dr. Mugdim Pašiƒ University of Delaware Sarajevo Graduate School of Business O ften our interest in data analysis
More informationToad for Data Analysts, Tips n Tricks
Toad for Data Analysts, Tips n Tricks or Things Everyone Should Know about TDA Just what is Toad for Data Analysts? Toad is a brand at Quest. We have several tools that have been built explicitly for developers
More informationTABLE OF CONTENTS. Creating an Account Why Use enewsletters. Setting Up an enewsletter Account. Create/Send Logging In.
ENEWSLETTER GUIDE TABLE OF CONTENTS Creating an Account Why Use enewsletters Setting Up an enewsletter Account 3 3 Create/Send Logging In Saved Drafts Creating a New Campaign Adding Content to a New Campaign
More informationExcel Budget Homework
Excel Budget Homework CSE 3, Fall 2009 Due at the BEGINNING of your next lab. A. Annual Budget One of the most common uses of a spreadsheet is to chart financial information. We are going to create an
More informationMicrosoft Excel. Qi Wei
Microsoft Excel Qi Wei Excel (Microsoft Office Excel) is a spreadsheet application written and distributed by Microsoft for Microsoft Windows and Mac OS X. It features calculation, graphing tools, pivot
More informationApache Configuration
Apache Configuration In this exercise, we are going to get Apache configured to handle a couple of different websites. We are just going to use localhost (the default address for a server), but the same
More informationKSTAT MINI-MANUAL. Decision Sciences 434 Kellogg Graduate School of Management
KSTAT MINI-MANUAL Decision Sciences 434 Kellogg Graduate School of Management Kstat is a set of macros added to Excel and it will enable you to do the statistics required for this course very easily. To
More informationPulling a Random Sample from a MAXQDA Dataset
In this guide you will learn how to pull a random sample from a MAXQDA dataset, using the random cell function in Excel. In this process you will learn how to export and re-import variables from MAXQDA.
More informationHelp File. Version 1.1.4.0 February, 2010. MetaDigger for PC
Help File Version 1.1.4.0 February, 2010 MetaDigger for PC How to Use the Sound Ideas MetaDigger for PC Program: The Sound Ideas MetaDigger for PC program will help you find and work with digital sound
More informationFusion Voicemail Plus User Guide For Android Devices
Welcome to Fusion Voicemail Plus! Fusion Voicemail Plus User Guide For Android Devices Fusion Voicemail Plus (FVM+) is a replacement for the ordinary voicemail that you use with your cellular phone company.
More informationStandard Deviation Estimator
CSS.com Chapter 905 Standard Deviation Estimator Introduction Even though it is not of primary interest, an estimate of the standard deviation (SD) is needed when calculating the power or sample size of
More informationIntroduction Course in SPSS - Evening 1
ETH Zürich Seminar für Statistik Introduction Course in SPSS - Evening 1 Seminar für Statistik, ETH Zürich All data used during the course can be downloaded from the following ftp server: ftp://stat.ethz.ch/u/sfs/spsskurs/
More informationGetting Started with Statistics. Out of Control! ID: 10137
Out of Control! ID: 10137 By Michele Patrick Time required 35 minutes Activity Overview In this activity, students make XY Line Plots and scatter plots to create run charts and control charts (types of
More information